Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A Note on Smoothing Distribution Function Estimation

  • Chu, In-Sun (Department of Mathematics, College of Natural Science, Dong-A University) ;
  • Choi, Jae-Ryong (Department of Mathematics, College of Natural Science, Dong-A University)
  • Published : 1997.12.01
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Abstract

The purpose of this paper is to consider the problem of selection of optimal smoothing parameter for kernel-type distribution function estimator, which asymptotically minimizes mean Hellinger distance.

Keywords

References

  1. Statistics and Probability Letters v.9 The Performance of Kernel Density Estimations in Kernel Distribution Function Estimation Jones, M. C.
  2. Statistics and Probability Letters v.18 Hellinger Distance and Kullback-Leibler Loss for the Kernel Density Estimator Kanazawa, Y.
  3. Theory of Probability and Application v.9 Some New Estimators for Distribution Function Nadaraya, E. A.
  4. Some Basic Theory for Statistical Inference Pitman, E. J. G.
  5. Communication Statistics-Theory and Methods v.17 Mean Integrated Squared Error Properties and Optimal Kernels When Estimating a Distribution Function Swanepoel, W. H.